1768 results about "Target surface" patented technology

The present application relates to a weld seam surface defect detection method and system. The weld seam surface defect detection method comprises: performing multi-angle and multi-surface acquisition of target surface images; then, reconstructing normal maps of the target surface images by means of a high-performance algorithm, and clarifying normal features of defects; and finally, on the basis of the surface normal features, aiming at transverse texture defects and height mutation defects, respectively designing a transverse texture defect detection algorithm based on two stages and rotated rectangle extraction and a height mutation defect detection algorithm based on adaptive dual-threshold segmentation. The present application overcomes texture noise and pseudo-defect interference of ground surfaces, effectively solves the problems of difficulty in feature extraction and positioning of ground surfaces of steel rail weld seams, and has the system operating efficiency superior to that of existing detection methods, thus satisfying requirements of actual production.

The invention relates to a remote sensing image ground feature recognition method based on deep learning, and the method comprises the steps: carrying out the data collection and preprocessing of a ground surface target region, eliminating the position deviation through geometric correction, processing the illumination difference through combination with radiation equalization, and generating a ground feature registration image; performing multi-dimensional feature fusion processing on the image, performing tensor fusion on vegetation spectral features, earth surface texture features, point cloud data features and linear ground feature features, and constructing a ground feature fusion matrix; a bilateral convolutional neural network is adopted to extract spectral response characteristics and spatial correlation characteristics, and characteristic interaction is realized through an attention mechanism to generate a ground feature probability distribution diagram; and finally, carrying out noise filtering, boundary refining and vectorization conversion processing on a classification result, and outputting a ground feature classification vector diagram. According to the method, three technical bottlenecks of insufficient cooperative utilization of multi-source heterogeneous data, insufficient spectrum-space feature fusion and poor GIS compatibility are solved, and the operation efficiency of territorial investigation, disaster monitoring and other scenes can be remarkably improved.

The invention discloses an unmanned aerial vehicle-mechanical arm system cooperative control method for precise spraying. According to the method, through a depth camera and a point cloud reconstruction algorithm, three-dimensional modeling of a target surface and semantic recognition of a spraying area are achieved, and a spraying path and spraying posture data are generated. Based on spraying task requirements, a spraying film thickness experience estimation model is established, and path point-level spraying parameters are obtained. Load mass change, mechanical arm mass center change and spraying reaction force of each path point are calculated, and a coupling dynamic model is constructed in combination with the system state. And dynamic compensation control input is generated by using an adaptive sliding mode control algorithm. After spraying is completed, the actual spraying effect is collected through image and point cloud detection, color, film thickness and texture features are extracted and compared with task requirements, error feedback is generated, and control parameters are adjusted online. According to the method, the problems of dynamic change and error compensation in the spraying process are effectively solved, and the method is suitable for a high-precision spraying task in a complex environment.

The invention discloses an error compensation inductance sensor calibration method and system, and the method comprises the steps: controlling a macro-micro composite driving platform to drive a moving part provided with a to-be-calibrated inductance sensor, and enabling the moving part to carry out the continuous displacement movement relative to a fixed standard target surface; measuring the actual displacement of the moving part to obtain a standard displacement sequence; the actual output voltage of the inductive sensor to be calibrated in the movement process is synchronously collected, and an actual measurement value sequence is formed; solving measurement deviation, generating a measurement deviation sequence, and dividing the sequence into not less than three compensation intervals according to a displacement range; a compensation value lookup table is established in each compensation interval, and calibration parameters used for correcting zero offset, gain drift and nonlinear characteristics are generated. Displacement measurement and sensor output synchronous acquisition are combined, zero offset, gain drift and non-linear errors can be corrected in a targeted mode, and compensation fineness and adaptability are improved.

The invention relates to the technical field of intelligent target scoring, in particular to an intelligent individual soldier target scoring system and method, and the system comprises a target surface calibration module, a hit recognition module, an offset mapping module, a mode switching module and a terminal output module. According to the method, the thermal expansion trend is analyzed by collecting the temperature data of the target surface sensor, the target surface can be calibrated more accurately, impact point positioning can be corrected, shooting target positioning can be optimized, the accuracy of the shooting result can be enhanced, hit points which are not consistent with the preset angle can be screened out by recording the stress vibration and ballistic characteristics of the target surface during shooting, and the accuracy of the shooting result can be improved. The authenticity and reliability of shooting data are effectively improved, the gun holding posture change of a shooter in continuous shooting is monitored, the posture change is associated with hit offset, the shooting posture is helped to be adjusted, the overall shooting precision is improved, the shooting mode is dynamically adjusted, the shooter can better adapt to different shooting environments, and the shooting efficiency is improved. And the pertinence and the effect of training are obviously improved.

The invention relates to the technical field of dispensing positioning, in particular to a trinocular vision-based five-axis dispensing machine and a precision calibration method thereof.The dispensing machine comprises an X-axis moving mechanism, a Y-axis moving mechanism, a Z-axis moving mechanism, an AC rotary workbench and a dispensing device, the Z-axis moving mechanism is provided with a first shooting assembly and a second shooting assembly, and the Z-axis moving mechanism is provided with a third shooting assembly and a fourth shooting assembly; a first calibration plate, a third shooting assembly and a second calibration plate are arranged on the AC rotary workbench; the precision calibration method comprises the following steps: S1, installing a camera; s2, camera self-calibration; s3, performing visual measurement on an X axis, a Y axis, a Z axis, an A axis and a C axis; s4, performing visual calibration; s5, comprehensive compensation is carried out, and the correction compensation effect is verified through real-time error correction and track retest; and S6, carrying out global iteration optimization strategy on the corrected and compensated actual pose model based on an LM algorithm. According to the invention, the stability of calibration precision can be ensured, the matching degree of a dispensing path and a target surface is improved, and high-precision dispensing is realized.

The invention discloses a projectile drop point detection method, system and equipment based on dual-light end-to-end fusion, and a medium. The method comprises the following steps: collecting visible light imaging data and thermal infrared imaging data of all target regions; preprocessing the data to obtain visible light and thermal infrared images of corresponding target region time-space registration; projecting a ground target area on the obtained image after space-time registration to a corresponding reference projection target surface; inputting the registered image into a multi-modal fusion detection model, and judging whether an explosion phenomenon is detected in the image frame by frame to obtain a bounding box corresponding to an explosion target in the image; according to the explosion bounding box, resolving and correcting the position of the drop point by adopting a drop point resolving algorithm, and determining the image coordinate of the drop point in the explosion area; and mapping the drop point to a reference projection target surface, obtaining position coordinate information of the drop point in the reference projection target surface, and recording and outputting relative position information of the drop point on the reference projection target surface. The detection precision is improved, and the target scoring task is completed.

The invention provides a passive radar seeker anti-interference identification method based on a dual-polarization array, and the method comprises the steps: obtaining a first signal and a second signal, and carrying out the time-space alignment calibration of the first signal and the second signal, and obtaining a first polarization signal and a second polarization signal; performing polarization-Doppler-frequency band three-dimensional tensor construction on the first polarization signal and the second polarization signal; performing dynamic core tensor decomposition processing on the polarization-Doppler-frequency band three-dimensional tensor to obtain a target polarization characteristic parameter and an interference polarization characteristic parameter; performing interference suppression processing on the first polarization signal and the second polarization signal through polarization matched filtering to generate an anti-interference enhanced signal; performing polarization scattering mechanism decomposition processing on the target polarization characteristic parameter to generate a target surface scattering component and a dihedral angle scattering component; and outputting an anti-interference identification result based on the target surface scattering component, the dihedral angle scattering component and the polarization phase consistency parameter of the anti-interference enhancement signal. The method can improve the anti-interference recognition precision of the radar.

The invention discloses a surface runoff cause identification method and device based on deep learning and interpretability analysis, and is used for solving the technical problem of low identification precision caused by the existing surface runoff cause identification method. The method comprises the following steps: acquiring meteorological and hydrological factor time series data, and inputting the meteorological and hydrological factor time series data into a surface runoff cause identification model based on deep learning; the surface runoff cause identification model based on deep learning comprises a one-dimensional convolution module, a bidirectional long short-term memory network and an identification module based on a multi-head attention mechanism. A one-dimensional convolution module is adopted to carry out convolution operation on the meteorological and hydrological factor time sequence data, and a local response feature sequence is output; performing bidirectional processing operation on the local response feature sequence through a bidirectional long-short-term memory network to generate a target comprehensive feature sequence; and inputting the target comprehensive feature sequence into an identification module based on a multi-head attention mechanism for identification, and outputting a target surface runoff cause identification result.

The invention relates to the technical field of robot control, and discloses a robot scanning path adjusting method, device, equipment and medium, and the method comprises the steps: controlling a robot equipped with a sensor to move along a preliminary path, collecting a preliminary two-dimensional image of a target object, processing the image, extracting the feature points of the target object, and combining the spatial information of the sensor when the image is collected; the method comprises the steps of generating a primary three-dimensional point cloud, determining a plurality of ideal sensor postures based on the primary three-dimensional point cloud, determining a new sensor position of each posture on a contactable surface to generate a re-planned scanning path, controlling a robot to move along the re-planned scanning path, adjusting the sensor postures, and collecting a final two-dimensional image of a target object. According to the method, the scanning path is optimized in combination with the initial three-dimensional point cloud local surface normal direction, so that the attitude of the sensor is matched with the geometrical characteristics of the target surface, the problem of three-dimensional reconstruction surface breakage caused by inter-frame pose mismatching under free breathing is solved, and the accuracy of autonomous ultrasonic scanning of the robot is improved.

The invention discloses a solar cell and a manufacturing method thereof, relates to the technical field of photovoltaic, and aims to increase the conductivity and effective doping concentration of a first part, covering at least part of the top of a pyramid-like pyramid, of a first semiconductor layer and facilitate reduction of transmission loss of carriers collected in the first semiconductor layer transmitted to a conductive material. The solar cell includes a semiconductor substrate and a first semiconductor layer. The semiconductor substrate comprises a first surface and a second surface which are opposite. At least one of the first surface and the second surface is a target surface. The surface of at least partial area of the target surface is a suede, and a plurality of similar pyramids are formed on the suede. The plurality of pyramids comprise a plurality of first pyramids, the first semiconductor layer is arranged on the textured surface, and the material of the first semiconductor layer comprises amorphous silicon and / or nano-crystalline silicon. The first semiconductor layer comprises a first part covering the top of the first-type pyramid and a second part covering the base of the first-type pyramid, and the crystallization degree of the first part is larger than that of the second part.

The invention discloses a polarization spectrum modulation type multispectral stereo imaging method which solves the problem that in the prior art, an existing polarization spectrum imaging scheme does not achieve three-dimensional reconstruction of a target and achieves the purpose that the three-dimensional reconstruction of the target is not achieved under the condition that active illumination or special marks are not needed. Synchronous high-precision reconstruction of physical attributes and three-dimensional geometry of the surface of the target is realized; the method comprises the following steps: uniformly modulating polarization information and spectral information of incident light of a target through a three-way optical filter and a polaroid to obtain modulated incident light information; performing aliasing acquisition of a plurality of polarization spectrum components on the modulated incident light information through a multi-color detector combination to obtain aliasing light intensity; performing linear solution on the aliasing light intensity to obtain each polarization spectrum component vector, calculating the polarization degree and the polarization angle of each channel, and further deriving a surface zenith angle and an azimuth angle; reconstructing the three-dimensional morphology of each spectrum channel through normal gradient field frequency domain integration; and finally, fusing the multi-spectral three-dimensional data to obtain a multi-spectral three-dimensional imaging result.

The invention relates to the technical field of robots and intelligent control, and discloses a robot trajectory control method, device and equipment based on multiple modalities and a medium, and the method comprises the steps: obtaining a natural language instruction, environment visual information and current state information of a robot, carrying out the fusion of visual and language features, and generating a fusion feature, generating a track sequence through a track generation model according to the fusion features and the robot state information, collecting a contact force signal of the tail end of the robot in contact with the target surface, adaptively adjusting impedance parameters by using the contact force signal, and generating a control instruction; and based on the contact force signal, feedback correction is carried out on the track generation model to drive the tail end of the robot to move, and multi-mode sensing and force control feedback cooperative control is achieved. According to the invention, track and force control cooperation is realized through multi-modal fusion and contact force feedback, so that the robot keeps stable fitting and adaptive motion in a complex contact scene, and the track generation precision and the imaging quality are improved.

The invention discloses a submarine topography reconstruction system and method based on optical mobile measuring and scanning, and relates to the technical field of ocean exploration, and the system comprises the following units: an image collection unit, which is used for coordinating the emission of 532nm pulse laser and the collection of a gating camera image through a synchronous sequential circuit, a triangulation measurement optical structure with separated emission and reception is adopted, and a submersible can be carried for mobile measurement and scanning; the system calibration unit is used for carrying out joint calibration on camera parameters and a laser plane so as to determine system calibration parameters, so that the spatial position of a laser stripe accurately corresponds to the actual coordinate of the target surface; and the image processing unit is used for preprocessing the image acquired by the system and further extracting the coordinates of the center line of the laser stripe in the preprocessed image. According to the invention, adjacent splicing can be carried out through continuously collected laser stripe images to construct two-dimensional submarine landform information, and three-dimensional reconstruction of submarine topography can be carried out by using generated point cloud data.

The invention relates to the technical field of X-ray tube control, and discloses a control method and device for a controllable flying focus X-ray tube, and the method comprises the steps: building an orthogonal electromagnetic deflection system based on an electron beam flight path of the X-ray tube, and the orthogonal electromagnetic deflection system comprises an X-direction electromagnetic coil and a Y-direction electromagnetic coil; creating a conversion relation for converting the target focus position function into an electromagnetic coil current value; executing nonlinear magnetic field response compensation to obtain high-speed switching control signals of the X-direction electromagnetic coil and the Y-direction electromagnetic coil; and performing focus trajectory prediction based on the high-speed switching control signal to obtain a focus motion trajectory formed by the electron beam on the target material, and performing thermal load distribution optimization on the focus motion trajectory to obtain a focus position control scheme for uniform distribution of the surface temperature of the target material. Accurate positioning control of the electron beam on the target material is achieved, and the X-ray imaging quality is improved.

An apparatus includes a first light source for illuminating a chart including an index surface on which an index is provided, an objective lens for guiding index light emitted from the chart to an optical system, a first element for receiving the index light reflected on an optical surface in the optical system, an interferometer configured to include a second light source and a second element, and acquire a wavefront of measurement light, the measurement light being test light reflected on the target surface, and a reduction unit for reducing an intensity of a signal of light reflected on an optical surface other than the target surface, of the test light reflected on the plurality of optical surfaces and received by the second element.

The invention relates to a polarization three-dimensional reconstruction method for solving zenith angle based on mixed reflected light. The method comprises the following steps: obtaining polarization images of a target in four directions of 0 degree, 45 degrees, 90 degrees and 135 degrees; respectively calculating the polarization degrees of the polarization images; obtaining a hybrid model of target surface reflected light, solving a zenith angle and an azimuth angle of the target, and obtaining a normal vector field of the target; based on the normal vector field of the target, the Frankot-Chellappa algorithm is used for integrating the normal vector field to obtain the three-dimensional depth map of the target, the method is suitable for outdoor natural light conditions, especially for three-dimensional reconstruction of offshore and long-distance targets, the limitation of a traditional method in a severe environment is overcome, and through efficient processing of the multi-angle polarization image, the depth map of the target is obtained. Dependence on a single light source and strict experiment conditions is reduced, and higher operation convenience and engineering practical value are achieved.

The invention discloses a projectile drop point detection method, system and equipment based on dual-light decision fusion, and a medium. The method comprises the following steps: collecting visible light and thermal infrared imaging data; preprocessing the data to obtain visible light and thermal infrared images of corresponding target region time-space registration; projecting a ground target area on the obtained image after space-time registration to a corresponding reference projection target surface; respectively inputting the registered images into a typical target detection model for target detection, judging whether an explosion phenomenon is detected in the images frame by frame, obtaining positioning information and category information in respective modes, dividing detection results into two categories of matched targets and unmatched targets, and outputting an explosion bounding box after secondary decision making; calculating and correcting the position of the drop point according to the explosion bounding box, and determining the image coordinate of the drop point; and mapping the coordinate of the drop point image to the reference projection target surface to obtain the position coordinate information of the drop point in the reference projection target surface. The method improves the detection precision, and better completes the target scoring task.

The invention relates to the technical field of machine vision detection, in particular to a surface defect detection method and system based on curved surface coding and multi-view fusion, and the method comprises the steps: constructing a curved surface coding illumination system, generating a coding light field, and projecting the coding light field to a target surface; synchronously acquiring reflection images of the coded light field through a multi-view imaging device, and obtaining a multi-dimensional view image data set; separating light components from the multi-dimensional view image data set, and extracting a defect feature set; performing multi-view information integration on the defect feature set to obtain comprehensive defect features; and performing defect judgment and parameter calculation on the target surface based on the comprehensive defect characteristics, and outputting a defect detection result. By adopting curved surface coding illumination and multi-view fusion, gradient information carried by a coding light field and multi-view imaging to supplement space details, accurate detection of surface and subsurface defects is realized, the adaptability to high-curvature and multi-reflection characteristic targets is improved, and the problem of insufficient detection precision of irregular reflective surface defects is solved.

The invention provides a multispectral radiation temperature measurement method and system, and belongs to the field of signal acquisition and processing in an infrared radiation temperature measurement technology. The problems of poor inversion precision and applicability of multispectral radiation temperature measurement are solved. The multispectral radiation temperature measurement method comprises the following steps of: measuring radiation information of the surface of a to-be-measured target by using a multi-wavelength pyrometer; the beam splitting system obtains radiation information of different spectrum channels; photoelectric conversion: converting the optical signal into an electric signal; constructing a target equation and a constraint optimization condition according to the brightness temperature model; carrying out multispectral data processing by utilizing an improved multi-population mixed pigeon inspired optimization algorithm; and the final real temperature and emissivity values are obtained. The device is mainly used for multispectral radiation temperature measurement.

The invention relates to a micro display device for a bifocal plane HUD (head up display) system, which solves the problems of halved field of view, limited working bandwidth, low color saturation and low brightness of the existing bifocal plane HUD system, and comprises an image display module and a polarization modulation element arranged above the image display module, the polarization modulation element is used for polarization modulation of display pixels, the effective area of the sub-wavelength medium grating arrangement is equivalent to a 1 / 2 wave plate, the display pixels are separated in a row-by-row or column-by-column staggered mode through the sub-wavelength medium grating arrangement, and the problem that the view field is halved due to an existing target surface space partitioning scheme is solved. The two adjacent sub-wavelength medium gratings convert incident light into linear polarization states in two directions, the two directions are mutually orthogonal, and the two spaced sub-wavelength medium gratings are completely the same, so that the two images are respectively adjusted into the mutually orthogonal linear polarization states, and the two images are generated in a staggered manner.

The invention relates to the technical field of solar cells, in particular to a laminated solar cell and a photovoltaic module. In the embodiment of the invention, the area of the orthographic projection of a first passivation contact layer on a reference surface is configured to be smaller than the area of the overlapping projection of a top cell unit and a bottom cell unit, and a first passivation layer is arranged on a first sub-surface exposed by the first passivation contact layer and a first target surface of the first passivation contact layer. The opposite side surfaces of the composite layer and the first passivation layer are in contact with each other, so that the efficiency of the battery can be improved.

The invention discloses an equipment on-line temperature measurement monitoring method based on thermal imaging, and relates to the technical field of on-line temperature measurement. The method comprises the following steps: synchronously acquiring reflection spectrum data and infrared thermal radiation data of a target surface through an integrated spectrum sensing module and a thermal imaging module; inverting the initial emissivity of the target area according to the reflection spectrum data based on Kirchhoff's law and a pre-stored material feature library; dynamically correcting the initial emissivity to generate a pixel-by-pixel corrected emissivity matrix; and carrying out pixel-by-pixel temperature calculation on the thermal imaging original data, constructing an equipment surface temperature distribution model, and carrying out abnormity early warning according to a preset threshold value. According to the method, through deep fusion of spectrum sensing and thermal imaging data, pixel-by-pixel emissivity calibration of complex surface equipment is realized, and the temperature measurement precision and reliability are remarkably improved.

The invention discloses a thin-wall structure layered body grid generation method based on surface grid alignment, which comprises the following steps of: reading an integral surface grid with a thin-wall structure characteristic and a mapping relation, and pairing a source surface grid and a target surface grid in the integral surface grid according to the mapping relation; aligning the source surface grid and the target surface grid which are paired, updating the target surface grid, and extracting triangular mapping information of an aligned region; according to the mapping information, advancing a source surface grid to a target surface grid layer by layer to obtain a layered body grid; extracting the outer surface of the stratified body mesh, combining the outer surface of the stratified body mesh with the overall surface mesh to obtain a combined surface mesh, and performing mesh point classification; normalizing the unit normal direction of the combined surface grid, calculating the normal direction at grid points needing to be propelled according to the grid point classification, and interpolating points according to distances in the normal direction to form a constraint point set; and generating a cavity area body grid by taking the constraint point set and the combined surface grid as constraints, and combining the cavity area body grid with the layered body grid to obtain the layered body grid of the overall thin-wall structure.

An inspection system and related methods that employ directional light for enhanced imaging are provided. The inspection system includes an inspection camera and at least one directional light source positionable in an offset position from a field of view of the inspection camera. The at least one directional light source is configured to emit directional light from the offset position into the field of view of the inspection camera so as to produce shadows on a surface of interest. Further, the inspection system includes a display device coupled to the inspection camera and the inspection camera is configured to capture one or more images of the shadows produced on the surface of interest. The display device is configured to receive and display the one or more images.

The invention relates to a red light therapeutic instrument real-time calibration method based on multi-modal data fusion, which comprises the following steps: firstly, collecting data such as optical power, target surface temperature, internal temperature, reflection spectrum and light source-target surface distance in a time window, and unifying time base alignment; performing anomaly elimination, de-noising and normalization on each modal data, and constructing a standardized data matrix; extracting multi-modal features through power spectral density, wavelet packet decomposition, exponential moving average and Kalman filtering, inputting the multi-modal features into a fusion network containing a modal special encoder and a cross-modal attention unit, and generating a red light treatment state vector; the driving current, the pulse width, the duty ratio, the emission angle and the aging compensation factor are solved in real time through constrained least square optimization and are issued to the driving control module, and the red light source is smoothly adjusted in a soft start mode; the system monitors the output power, calibration is completed if the output power meets a threshold value, and otherwise, the next iteration is started. According to the method, power closed-loop correction can be realized, and dose consistency and thermal safety are improved.

The invention belongs to the technical field of automatic driving, and particularly relates to a 4D millimeter wave radar and camera fusion three-dimensional target detection method based on surface parameter estimation guidance. According to the method, information of an image and point cloud is effectively combined through an explicit target surface depth fitting model, the target surface depth is fitted, then accurate estimation of the three-dimensional space position of the target is achieved, and dense three-dimensional space information is obtained based on surface depth estimation in a subsequent module, so that accurate estimation of the three-dimensional space position of the target is achieved. And visual angle conversion of image features and feature extraction of false point cloud spatial position information are guided, so that the performance of a target detection algorithm is greatly improved.

The invention discloses a partial discharge intelligent detection method and a partial discharge intelligent detection system. The method comprises the following steps: firstly, synchronously acquiring a multi-channel ultrasonic signal and a surface infrared image sequence of to-be-detected power equipment; performing pulse detection, cross-channel clustering based on a sliding time window and time difference positioning on the ultrasonic signal to obtain a preliminary discharge point; the multi-moment infrared images are intelligently selected and fused based on the ultrasonic pulse active time period, and a target surface infrared image highlighting the abnormal temperature rise area is generated; performing spatial aggregation on the ultrasonic positioning point and the infrared abnormal region to form a suspected sound-heat associated discharge source; respectively extracting waveform features and temperature features from the aggregated ultrasonic pulse set and the infrared region, fusing the waveform features and the temperature features, and inputting the fused features into a dual-channel neural network model; and finally, the model outputs a discharge type identification result and a discharge intensity evaluation value of the suspected discharge source. According to the invention, through deep space-time fusion and feature level fusion, the positioning precision and identification accuracy of partial discharge detection are significantly improved.

The invention provides a wind power blade web detection method and a related device, and relates to the technical field of detection. The method comprises the steps that terahertz time domain data of a web to be detected are obtained to serve as first sample data, terahertz time domain data of a metal layer are obtained to serve as first reference data, and the terahertz time domain data are obtained through a probe; the distance between the probe and a first target surface, facing the probe, of the to-be-detected web is equal to the distance between the probe and a second target surface, facing the probe, of the metal layer; performing Fourier transform on the first sample data and the first reference data to obtain second sample data and second reference data; according to the second sample data and the second reference data, performing deconvolution on the second sample data to obtain third sample data; performing noise reduction processing on the third sample data to obtain target sample data; and according to the target sample data, generating a cross-section image of the to-be-detected web. In this way, a cross-sectional image capable of performing high-precision display on levels and defects can be obtained.

The invention provides a signal processing method and system for a long-distance follow-up laser seeker, and belongs to the technical field of signal processing. Target surface center coordinates, a light spot image sequence and a synchronous echo pulse waveform sequence of the seeker are obtained; the speckle energy entropy and the centroid drift distance are obtained by calculating the information entropy and the centroid displacement of the target light spot image, and the pulse width parameter is extracted from the echo waveform. And constructing the three parameters into a laser feature vector, and inputting the laser feature vector into a pre-trained reflecting surface classification model so as to identify the surface material type of a laser irradiation point in real time. And determining a group of optimal follow-up control gain sets from the material gain mapping relation according to the surface material type, and dynamically reconstructing a follow-up control loop by using the optimal follow-up control gain sets. And the sight angle error of the light spot mass center and the target center is calculated, and the adjusted control loop is used for calculating the error to generate an accurate driving instruction signal, so that the tracking stability and the tracking precision of the target are improved.